Honors and Awards
- NSF CAREER Award, National Science Foundation, 2026
- Structural Engineering Doctoral Dissertation Fellowship, UCSD, 2017
- Graduate National Scholarship, 2012
- Qian Ling-Xi Mechanics Scholarship, 2012
Selected Publications
Du, H., & He, Q. (2026). JAX-MPM: A learning-augmented differentiable meshfree framework for GPU-accelerated Lagrangian simulation and geophysical inverse modeling. Engineering with Computers.
Guo, B., Lin, Z., & He, Q. (2025). History-aware neural operator: Robust data-driven constitutive modeling of path-dependent materials. Computer Methods in Applied Mechanics and Engineering.
Du, H., Guo, B., & He, Q. (2025). Differentiable neural-integrated meshfree method for forward and inverse modeling of finite-strain hyperelasticity. Engineering with Computers, 41, 1597–1617.
Du, H., & He, Q. (2024). Neural-Integrated Meshfree (NIM) method: A differentiable programming-based hybrid solver for computational mechanics. Computer Methods in Applied Mechanics and Engineering, 427, 117024.
He, Q., Perego, M., Howard, A. A., Karniadakis, G. E., & Stinis, P. (2023). A Hybrid Deep Neural Operator/Finite Element Method for Ice-Sheet Modeling. Journal of Computational Physics, 492, 112428.
Du, H., Zhao, Z., Cheng, H., Yan, J., & He, Q. (2023). Modeling density-driven flow in porous media by physics-informed neural networks for CO2 sequestration. Computers and Geotechnics, 159, 105433.
He, X., He, Q., & Chen, J. S. (2021). Deep autoencoders for physics-constrained data-driven nonlinear materials modeling. Computer Methods in Applied Mechanics and Engineering, 385, 114034.
He, Q., & Tartakovsky, A. M. (2021). Physics‐Informed neural network method for forward and backward advection‐dispersion equations. Water Resources Research, 57(7), e2020WR029479.
Kaneko, S., Wei, H., He, Q., Chen, J. S., & Yoshimura, S. (2021). A hyper-reduction computational method for accelerated modeling of thermal cycling-induced plastic deformations. Journal of the Mechanics and Physics of Solids, 151, 104385.
He, Q., Laurence, D., Lee, C. H., Chen, J. S. (2020). Manifold learning-based data-driven modeling for soft biological tissues. Journal of Biomechanics, 110124.
He, Q., Barajas-Solano, D., Tartakovsky, G., Tartakovsky, A. (2020) Physics-Informed Neural Networks for Multiphysics Data Assimilation with Application to Subsurface Transport. Advances in Water Resources, 141, 103610.
He, Q. & Chen, J. S. (2019) A Physics-Constrained Data-Driven Approach Based on Locally Convex Reconstruction for Noisy Database. Computer Methods in Applied Mechanics and Engineering, 363, 112791.
He, Q., Chen, J. S., & Marodon, C. (2019). A decomposed subspace reduction for fracture mechanics based on the meshfree integrated singular basis function method. Computational Mechanics, 63(3), 593- 614.
He, Q., Wei, H., Chen, J. S., Wang, H. P., & Carlson, B. E. (2018). Analysis of hot cracking during lap joint laser welding processes using the melting state-based thermomechanical modeling approach. The International Journal of Advanced Manufacturing Technology, 94(9-12), 4373-4386.
He, Q., Kang, Z., & Wang, Y. (2014). A topology optimization method for geometrically nonlinear structures with meshless analysis and independent density field interpolation. Computational Mechanics, 54(3), 629-644.
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